A Conceptual Framework for Selecting and Analyzing Stressor Data to Study Species Richness at Large Spatial Scales

/ In this paper we develop a conceptual framework for selectingstressor data and analyzing their relationship to geographic patterns ofspecies richness at large spatial scales. Aspects of climate and topography,which are not stressors per se, have been most strongly linked withgeographic patterns of species richness at large spatial scales (e.g.,continental to global scales). The adverse impact of stressors (e.g., habitatloss, pollution) on species has been demonstrated primarily on much smallerspatial scales. To date, there has been a lack of conceptual developmenton how to use stressor data to study geographic patterns of speciesrichness at large spatial scales.The framework we developed includes four components: (1) clarification of theterms stress and stressor and categorization of factors affecting speciesrichness into three groups-anthropogenic stressors, natural stressors, andnatural covariates; (2) synthesis of the existing hypotheses for explaininggeographic patterns of species richness to identify the scales over whichstressors and natural covariates influence species richness and to providesupporting evidence for these relationships through review of previousstudies; (3) identification of three criteria for selection of stressor andcovariate data sets: (a) inclusion of data sets from each of the threecategories identified in item 1, (b) inclusion of data sets representingdifferent aspects of each category, and (c) to the extent possible, analysisof data quality; and (4) identification of two approaches for examiningscale-dependent relationships among stressors, covariates, and patterns ofspecies richness-scaling-up and regression-tree analyses.Based on this framework, we propose 10 data sets as a minimum data base forexamining the effects of stressors and covariates on species richness atlarge spatial scales. These data sets include land cover, roads, wetlands(numbers and loss), exotic species, livestock grazing, surface water pH,pesticide application, climate (and weather), topography, and streams.KEY WORDS: Anthropogenic impacts; Biodiversity; Environmental gradients;Geographic information systems; Hierarchy     

ENVIRONMENTAL AUDITING: An Approach for Characterizing Tropospheric Ozone Risk to Forests

/ The risk tropospheric ozone poses to forests in the United States is dependent on the variation in ozone exposure across the distribution of the forests in question and the various environmental and climate factors predominant in the region. All these factors have a spatial nature, and consequently an approach to characterization of ozone risk is presented that places ozone exposure-response functions for species as seedlings and model-simulated tree and stand responses in a spatial context using a geographical information systems (GIS). The GIS is used to aggregate factors considered important in a risk characterization, including: (1) estimated ozone exposures over forested regions, (2) measures of ozone effects on species' and stand growth, and (3) spatially distributed environmental, genetic, and exposure influences on species' response to ozone. The GIS-based risk characterization provides an estimation of the extent and magnitude of the potential ozone impact on forests. A preliminary risk characterization demonstrating this approach considered only the eastern United States and only the limited empirical data quantifying the effect of ozone exposures on forest tree species as seedlings. The area-weighted response of the annual seedling biomass loss formed the basis for a sensitivity ranking: sensitive-aspen and black cherry (14%-33% biomass loss over 50% of their distribution); moderately sensitive-tulip popular, loblolly pine, eastern white pine, and sugar maple (5%-13% biomass loss); insensitive-Virginia pine and red maple (0%-1% loss). In the future, the GIS-based risk characterization will include process-based model simulations of the three- to 5-year growth response of individual species as large trees with relevant environmental interactions and model simulated response of mixed stands. The interactive nature of GIS provides a tool to explore consequences of the range of climate conditions across a species' distribution, forest management practices, changing ozone precursors, regulatory control strategies, and other factors influencing the spatial distribution of ozone over time as more information becomes available.KEY WORDS: Ecological risk assessment; GIS; Ozone; Risk characterization; Forests; Trees     

支持灾害管理决策的咨询信息系统

为减少中国大城市灾害造成的损失，运用信息科学、系统科学的方法和计算机技术，建立支持灾害管理决策的咨询信息系统（ＤＭＤＳＣＩＳ）。灾害文献数据库管理系统（ＤＬＤＢＭＳ）是这一咨询信息系统的知识基础和信息来源。本文论述了“ＤＬＤＢＭＳ”和三个主要的子系统“灾害文献数据库管理系统”、“灾害事实数据库管理系统”、“中外减灾法规超文本检索系统”的作用、设计思想、构成、功能和实现方法。     

矿井重大灾害危险性评价的改进灰色统计法

用灰色统计理论［１］研究了矿井四大灾害即冒顶、水灾、火灾和瓦斯爆炸的危险性预评价问题，提出了一种新的评价方法──灰色统计综合法。同时，从应用的角度出发对灰色统计的算法作了改进，改进后的算法便于记忆和应用。     

Changes in risk perception among North Sea offshore personnel in the period 1990 to 1994

A self-completion questionnaire survey was carried out among employees on offshore oil platforms in the Norwegian part of the North Sea in February 1990 and repeated in February 1994. A total of 915 employees on eight platforms (five oil companies) answered the questionnaire in 1990 and the response rate was 92%. In 1994, 1138 respondents on twelve platforms and nine companies filled in the questionnaire. The response rate was 87%. Significantly fewer of the personnel felt at risk in 1994 compared to 1990. Likewise, a greater percentage of the employees were satisfied with safety and contingency measures, and experienced job stress to a lesser extent in 1994 than they did in 1990.     

Using digital image projections to visualize forest landscape changes due to management activities and forest growth

A pedagogic problem in forestry and landscape management is to visualize future landscape effects of forest growth and current management activities in the forest. This paper presents a method for forecasting digital image projections of forest landscape dynamics. Static nonlinear regression functions estimate the digital numbers in a Landsat Thematic Mapper image. Regressors used are forest stand variables. By estimating the future forest stand data, based on intermediate treatment and growth, future satellite digital images are created. In a case study example, the future landscape of a forest block in the province of Västernorrland, Sweden, is projected to demonstrate the application of this visualization technique.     

淮河上游洪水灾害可公度信息系预测

可公度信息系是一种源于天文学的预测方法，其实质是寻求事物发生的经验关系。本文应用此法对淮河上游的洪水灾害进行了预测分析，结果表明淮河上游洪水灾害发生具有２ａ、４ａ、５ａ、７ａ、９ａ、１１ａ、１９ａ及７１ａ等多种周期，并在１９９７年、２０００年等年份的前后有可能发生大洪水。     

建筑物火灾危险性评估的一种工程方法

提出了建筑物火灾危险性评估的一种工程方法。该方法基于建筑火灾的区域模拟理论和人员疏散的最新研究成果，分别计算出火灾中达到危险状态的时间和整个疏散过程所需的时间，通过对比这两个时间，来确定火灾危险性的大小。这种方法概念清晰，简单易行，能在一定程度上对实际建筑物的火灾危险性进行评估，也可用于对火灾的安全工程设计评价和安全咨询。     

加强环境信息工作的对策探讨

根据环境信息工作直接、及时、针对性强等特点和发展趋势，有的放矢地提出了强化意识，提高信息质量，深入调研，进一步加强环境信息工作的对策。     

"双主模式"在课程整合中的应用

信息技术与课程整合的实施是强调在各学科的教学过程中积极运用信息技术.大部分学校的实践过程中还是普遍存在着这样那样的误区.将“双主模式“教学设计理论作为信息技术与课程整合的指导思想,体现学生的主体性,发挥教师的主导作用.